"No chance": how inexperienced traders lose money in prediction markets to "sharks"

Most of the profits in the forecast markets, where Polymarket and Kalshi platforms dominate, go to professionals who are willing to pay for access to specialized data and use trading algorithms, WSJ writes. Inexperienced traders guided by open-source information or intuition tend to lose money.

- 67% of all profits on Polymarket came from just 0.1% of accounts, according to the publication's analysis of the platform's data. This means that the total winnings of almost $500 million were shared by less than 2,000 traders. WSJ analyzed 1.6 million accounts on Polymarket that have traded since November 2022. In total, there are at least 2.3 million accounts registered on the site;

- more than 70% of Polymarket users lose money, writes WSJ. The typical user loses between $1 and $100, while the least successful 10% of traders lose an average of $4,000 each, the analysis shows. Polymarket declined to comment;

- on the Kalshi platform, the number of users losing money also far exceeds the number of users making money. According to the company's own estimates, in April, for every profitable user there were 2.9 unprofitable ones, Kalshi spokeswoman Elizabeth Diana said.

Polymarket and Kalshi position themselves as tools that can change the lives of ordinary people and give an equal chance of success. But for most users, the reality is different, the WSJ writes. Prediction markets are increasingly attracting professional firms with dozens of employees whose goal is to beat the students, gamblers and small traders who make up the majority of the audience of these platforms.

The presence of inexperienced traders without access to big data in the markets serves as a powerful incentive for more sophisticated participants to enter, which ultimately leads to more accurate forecasts, former Kalshi employee Adhi Rajaprabhakaran told WSJ. In a blog post on Substack last year, he referred to casual traders as "fish" - player slang for inexperienced participants doomed to lose money.

To get an edge, professionals pay for access to big data from third-party vendors. Computers use this data and algorithms to predict price movements and manage risk faster than humans can. The scale of the firms also allows them to make frequent trades - sometimes tens of thousands a day - and lock in profits gradually, exhibiting a discipline rarely seen in novices.

For example, former Princeton student Samuel Wood-Soloff founded such a company with four friends with $500,000 from crypto startup gas pedal Alliance Capital. The company bets on sports, politics and the value of cryptocurrencies. Wood-Soloff declined to disclose profits or losses, only saying they have placed between $500,000 and $1 million on Polymarket, Kalshi and smaller platforms.

Student Jonathan Stull-Ryan is the co-founder of another firm that is one of the top five traders in terms of betting on cryptocurrency prices on Kalshi. The company employs about a dozen people - all students. According to Stull-Ryan, the firm has turned $1,000 into a seven-figure sum. The company spends more than $200,000 a year on real-time data streams, AI programming agents and servers, and uses algorithms to make tens of thousands of trades a day.

Inexperienced traders "don't stand a chance," says former professional poker player Michael Boss. He got serious about trading about three months ago and has since earned more than $668,000 on Kalshi, mostly from sports betting. Boss makes 60 trades a minute and adjusts his buy and sell orders 30 times a second.

Inexperienced traders on Kalshi are simply betting on what they hope will happen, he says. "That's not how it works in cryptocurrencies or the stock market where people trade securities," Boss says.

Professional traders tend to avoid bets in which they can't get a sure advantage, the WSJ writes. An example is the mentions market, where traders bet on whether a famous person will utter a certain word in a speech or public appearance. WSJ's analysis of Kalshi data shows that bets on mentions win significantly less often than participants expect based on the reported odds. After examining more than 35,000 completed mention contracts, the publication found: on average, "yes" bets with a stated probability of winning of 50% are profitable only about 40% of the time. Since contract prices must match their probabilities, punters are actually overpaying, the WSJ writes.

The publication describes the story of John Pederson, a 33-year-old chef from Detroit who lost his job after a car accident. After taking out a loan, he started betting on Kalshi - first on snowfall amounts, then on sporting events - and managed to earn $41,000. In January, however, he lost all his money.

Pederson bet the entire amount on whether performer A$AP Rocky would utter the word "rapper" during an appearance on "The Jimmy Fallon Tonight Show." If he won, he could receive more than $168,000. In the full version of the interview posted on YouTube, the musician did say the word - but that segment was cut from the TV broadcast. According to Kalshi's rules, only what was said on air counts - and Pederson was left with nothing.

This article was AI-translated and verified by a human editor